The transformative potential of data and image analysis for eye care

Introduction to the event from lead organiser Professor Emanuele Trucco, University of Dundee

Healthcare is arguably the last major industry to be transformed by the information age.  Deployments of information technology have only scratched the surface of possibilities for the potential influence of information and computer science on the quality and cost-effectiveness of healthcare. In this talk, the opportunities provided by computer science and "big data" to transform health care delivery models will be discussed. Examples will be given from nationwide research and development programmes that integrate electronic patient records with biologic and health system data. Two themes will be explored; specifically:

1) How the size of the UK (65M residents), allied to a relatively stable population and unified health care structures facilitate the application of health informatics to support nationwide quality-assured provision of diabetes care.

2) How population-based datasets and disease registries can be integrated with biologic information to facilitate (i) epidemiology; (ii) drug safety studies; (iii) enhanced efficiency of clinical trials through automated follow-up of clinical events and treatment response; and, (iv) the conduct of large-scale genetic, pharmacogenetics, and family-based studies essential for precision medicine.

The last two decades, and in particular the last five years, have witnessed an explosion in the development of new imaging technologies. A significant advance is the availability of higher speed, higher resolution, and deeper penetrating swept source OCT technology which allows retinal disease to be studied in an en face plane in a depth-resolved fashion. Adaptive optics techniques have further advanced the axial resolution of our imaging technologies. Other major advances included enhances in contrast, facilitating molecular and functional imaging such as hyperspectral imaging, quantitative autofluroescence, fluorescence lifetime imaging ophthalmoscopy, and OCT angiography.  Mutlidimensional analysis techniques are being developed to cope with these enormous amounts of data. Imaging technology has also benefited from the introduction of widefield devices with specialized mirrors and optics allowing the entire retina to be photographed in a single acquisition. Widefield imaging has provided new insights into various diseases including diabetic retinopathy. Recent studies have highlighted the prognostic importance of peripheral lesions in diabetic retinopathy, with eyes with predominantly peripheral disease having a four-fold higher risk of progression. Combining widefield imaging with artificial intelligence/deep learning approaches, it is now possible to automatically identify and classify diabetic retinopathy, which may have significant public health applications in diabetic retinopathy screening programs.

Ophthalmology has one of the fastest growing imaging arsenal. With these new technologies nearly all components of the human eye can now be imaged. It is a major undertaking to make sure that all imaging modalities are scientifically evaluated for their validity and clinical utility. However, novel clinical imaging modalities raise new, often unexpected questions. These can only be answered by incorporating laboratory research into the evaluations which, in turn, lead to better understanding of the clinical phenotypes. Humans have an incredible ability to recognise patterns and with the new imaging modalities being high enough quality, new patterns are continuously emerging. Therefore, image analysis is still predominantly done manually. As such it is fraught with slow reporting and the need for ever increasing attention to detail.  There is risk of not recognizing crucial features contained in the images leading to the recording of wrong phenotype. Therefore, if we are to cope with the amount of images we generate, there is a need for intelligent, automated, non-human based, though probably human supervised, image analysis.  It is very likely that the development of new algorithms will lead to the development of new treatment paradigms to benefit the patients.

UK Biobank was initially conceived as a platform for studies of gene environment interaction in major chronic diseases of older age, such as cancer, stroke, MI and diabetes. Towards the end of the study, the UKBB steering committee advised the broadening of the scope of the study to include more detailed examination of participants, including assessment of physical fitness, brain and cardiac imaging, as well as an examination of eyes and vision. Moorfields Eye Hospital and the UCL Institute of Ophthalmology in London developed the eye and vision module. The core funding for the examination was provided by the Wellcome Trust, The Medical Research Council and The Department of Health. Additional support for training, implementation and quality control came from the NIHR Biomedical Research Centre at Moorfields Eye Hospital.
117,649 people took part in the basdeline eye and vision component of UK Biobank, undergoing modified logMAR visual acuity testing on a computerized system developed specifically for UK Biobank, autorefraction and keratometry (Tomey RC-5000), as well as measurement of intraocular pressure on a Reichert ORA Ocular Response Analyser, which returns measures of Goldmann equivalent intraocular pressure (IOP), corneal hysteresis, corneal resistance factor and IOP adjusted for corneal biomechanical properties. A smaller number (68,151) underwent simultaneous colour retinal photography, together with spectral domain optical coherence tomography (SD-OCT) in both eyes. During the data collection phase of UKBB, the Image Reading Centre at Moorfields provided a rapid turn-around quality assurance service for the macular photos and OCT images, finding them to be of high quality, compared with other studies using similar methodology. This large scale, well-curated eye data, together with accompanying extensive phenotyping of all major organ systems, make the UK Biobank eye and vision dataset unique worldwide.
Eye and vision researchers around the UK have formed a consortium involving clinicians and academics from around the UK, incorporating Belfast, Bristol, Cambridge, Cardiff, Dundee, Edinburgh, Gloucester, Leeds, Manchester, Newcastle, Nottingham, Southampton, St Andrews, Warwick and several London centres (Brunel, Imperial, Kings, Moorfields, UCL, St Georges). The consortium interacts using UK Universities JISCMail email list server. The group meets in February each year for a day-long programme of planning, discussion and debate. This has led to the formation of groups working on various aspects of data, including visual acuity, refractive error, intraocular pressure, retinal vascular characteristics, genetics and outcomes adjudication and monitoring. Multiple publications have ensued, with two major genetics studies in press in Nature Genetics. 

The Northern Ireland Cohort for Longitudinal Aging Study is a comprehensive, long-term epidemiological study of adult development and ageing which started in February 2014 and consists of a random sample of men and women aged 50 years, representative of the Northern Ireland population.  As part of the study approximately 3,600 participants have attended the Wellcome-Wolfson Clinical Research Facility (CRF) at Belfast City Hospital for a health assessment.  The health assessment included anthropometry, respiratory, cardiovascular, cognitive and ophthalmology tests. The ophthalmic component involved visual acuity, auto refraction, corneal compensated intra-ocular pressure, stereo colour fundus photographs, infra-red and autofluorescent retinal images, wide field Optos colour images and Spectral Domain Optical Coherence Tomography (OCT) with Enhanced Depth Imaging (EDI) of the choroid. Macular pigment was also assessed using dual-wavelength autofluorescence. To date most epidemiological studies have only used colour fundus photographs for estimating ocular disease prevalence.  The talk will discuss the opportunities and challenges of using multi-modal imaging and incorporating the data into a larger framework that also encompasses genomic, epigenomic, dietary and biochemical biomarkers.D

Facilitated open discussion: imaging, data and vision- priorities for collaboration, research and eye health.

Led by Michael Bowen, College of Optometrists